ShannonBeta {entropart} | R Documentation |

## Shannon beta entropy of a community

### Description

Calculates the Shannon beta entropy of a community belonging to a metacommunity.

### Usage

```
ShannonBeta(NorP, NorPexp = NULL, ...)
bcShannonBeta(Ns, Nexp, Correction = "Best", CheckArguments = TRUE)
## S3 method for class 'ProbaVector'
ShannonBeta(NorP, NorPexp = NULL, ...,
CheckArguments = TRUE, Ps = NULL, Pexp = NULL)
## S3 method for class 'AbdVector'
ShannonBeta(NorP, NorPexp = NULL, Correction = "Best", ...,
CheckArguments = TRUE, Ns = NULL, Nexp = NULL)
## S3 method for class 'integer'
ShannonBeta(NorP, NorPexp = NULL, Correction = "Best", ...,
CheckArguments = TRUE, Ns = NULL, Nexp = NULL)
## S3 method for class 'numeric'
ShannonBeta(NorP, NorPexp = NULL, Correction = "Best", ...,
CheckArguments = TRUE, Ps = NULL, Ns = NULL, Pexp = NULL, Nexp = NULL)
```

### Arguments

`Ps` |
The probability vector of species of the community. |

`Pexp` |
The probability vector of species of the metacommunity. |

`Ns` |
A numeric vector containing species abundances of the community. |

`Nexp` |
A numeric vector containing species abundances of the metacommunity. |

`NorP` |
A numeric vector, an integer vector, an abundance vector ( |

`NorPexp` |
A numeric vector, an integer vector, an abundance vector ( |

`Correction` |
A string containing one of the possible corrections: currently, |

`...` |
Additional arguments. Unused. |

`CheckArguments` |
Logical; if |

### Details

The derivation of Shannon beta entropy can be found in Marcon *et al.* (2012).

Bias correction requires the number of individuals to estimate sample `Coverage`

. Use `bcShannonBeta`

and choose the `Correction`

.

The functions are designed to be used as simply as possible. `ShannonBeta`

is a generic method. If its first argument is an abundance vector, an integer vector or a numeric vector which does not sum to 1, the bias corrected function `bcShannonBeta`

is called. Explicit calls to `bcShannonBeta`

(with bias correction) or to `ShannonBeta.ProbaVector`

(without correction) are possible to avoid ambiguity. The `.integer`

and `.numeric`

methods accept `Ps`

or `Ns`

arguments instead of `NorP`

for backward compatibility.

### Value

A number equal to the calculated entropy.

### References

Marcon, E., Herault, B., Baraloto, C. and Lang, G. (2012). The Decomposition of Shannon's Entropy and a Confidence Interval for Beta Diversity. *Oikos* 121(4): 516-522.

Zhang, Z. and Grabchak M. (2014). Nonparametric Estimation of Kullback-Leibler Divergence. *Neural computation* 26(11): 2570-2593.

### See Also

### Examples

```
# Load Paracou data (number of trees per species in two 1-ha plot of a tropical forest)
data(Paracou618)
# Ps is the vector of probabilities
Ps <- as.ProbaVector(Paracou618.MC$Ps)
# Probability distribution of the first plot
Ps1 <- as.ProbaVector(Paracou618.MC$Psi[, 1])
# Shannon beta entropy of the plot
ShannonBeta(Ps1, Ps)
# Ns is the vector of abundances of the metacommunity
Ns <- as.AbdVector(Paracou618.MC$Ns)
# Abundances in the first plot
Ns1 <- as.AbdVector(Paracou618.MC$Nsi[, 1])
# Reduced-bias estimator of Shannon beta entropy of the plot
bcShannonBeta(Ns1, Ns)
```

*entropart*version 1.6-13 Index]